How MT Cells Compute the Motion of Visual Patterns
Speaker: Dr. Nicole Rust , McGovern Institute for Brain Research
Neurons in area MT are selective for the direction of visual motion. In addition, many MT cells are tuned for the global motion of a compound stimulus invariant of the motion components that comprise it, a behavior not seen in earlier visual areas. In this talk, I will demonstrate that this invariance can be captured by a model similar to the one proposed by Hubel and Wiesel to describe the construction of orientation tuning in V1. The "cascade" model that I will present describes an MT cell as summing the afferent responses of a population of nonlinear V1 cells, followed by a simple nonlinearity to capture thresholding. Fits of the model using extensions of classical reverse correlation techniques show that it robustly predicts the separately measured responses to gratings and plaids. The model also captures the full range of invariance across MT cells. Invariant cells that signal pattern motion are distinguished by convergent excitatory input from V1 cells with a wide range of preferred directions, strong motion opponent suppression and a tuned normalization that may reflect suppressive input from the surround of V1 cells.